The invention is particularly useful in the field of wireless digital communications systems. In these systems, one usually deals with multipath channels: due to reflections on obstacles, the transmitted signal reaches the receiver after having followed a plurality of paths. Hence the received signal results from the superposition of a plurality of replica of the transmitted signal, each one associated (in the equivalent complex baseband representation) with a specific delay and attenuation. This received signal is therefore equal to the convolution of the transmitted signal with a so-called Channel Impulse Response (CIR) h(t) (where t denotes time).
The CIR is non-zero only in an interval 0<t<τ, where τ is the so-called excess delay of the channel, viz., the maximum possible delay between the various paths. The channel is said to be time-dispersive if the shape of the CIR is different from one narrow peak. Typical values of τ range from 50 to 150 ns for in-door communications, and from 250 ns to 30 μs for mobile radio communications.
Equivalently, implementing a Fourier transform of the CIR, the time-dispersion properties of a channel may be represented in the “frequency domain” by means of a “channel transfer function” H(f); at any given frequency, the value of this function is called the “Channel Transfer Factor” (CTF).
The data symbols to be transmitted are modulated, and the receiver demodulates the corresponding received signal in order to recover those symbols. Clearly, knowledge of the CIR allows one to conduct this demodulation more accurately.
Furthermore, in many modern digital communications systems, for example telephone systems or mobile radio systems, the demodulation process is “coherent”. This requires that the system provides a means for “channel estimation”, viz., for computing an estimate of some channel characteristics of interest (such as the channel impulse response) using a reference portion of the received signal. For example, in so-called pilot-assisted channel estimation, one transmits a “pilot signal” based on symbols which are a priori known by the receiver. As another example, in so-called decision-directed channel estimation, the receiver uses as a reference some received symbols whose value has been determined by means of a tentative decision process.
A realistic channel always suffers from random noise, which adds up to the ideally-noiseless received signal. Therefore, if channel estimation is purely based on reference symbols, one only obtains a coarse channel estimate, so that the coherent demodulation process based on this estimate will offer sub-optimal performance. In order to improve over such coarse estimates, it is often necessary to take into account known statistical properties of the channel and/or the noise process. Channel variations over time or over frequency have typically a smaller bandwidth than the noise process, so that, for example, some known channel estimation methods use a filter in order to reduce the amount of noise afflicting the channel estimates.
The need for channel estimation arises, for example, in communications systems using Orthogonal Frequency-Division Multiplexing (OFDM).
OFDM is a multiple-channel modulation scheme. It is especially appropriate for highly frequency-selective channels such as typical channels for mobile communications, or for high-rate wireline transmission over copper lines. Such channels are characterized by impulse responses which are substantially longer than one sample interval. This means that, even in the noiseless case, each received sample in the digital baseband domain is a superposition of multiple transmitted samples weighted by the appropriate channel coefficients. In order to resolve such “intersample interference”, some kind of equalization needs to be performed.
The way OFDM combats intersample interference is by dividing the total channel bandwidth into a number D of substantially smaller portions, called subchannels. One OFDM channel comprises one parallel use of all subchannels. The data to be transmitted is collected into so-called OFDM symbols, and each OFDM symbol is transmitted in parallel on a number Du (0<Du≦D) of these subchannels. The transmitted subchannel signals are orthogonal to each other. Since the duration of one OFDM symbol is much longer than the sample interval, the problem of intersymbol interference is strongly reduced.
To get totally rid of intersymbol interference, a guard interval between two symbols is usually introduced during OFDM transmission. If the length of the guard interval exceeds the length of the channel impulse response, there is no residual intersymbol interference. Furthermore, if the guard interval is used in the form of a cyclic prefix, as is usually the case for OFDM transmission, one may implement a very simple equalization of the frequency-selective channel in the frequency domain.
The Wireless Local Area Networks (WLAN) systems are examples of radio communications systems which use OFDM. ETSI (European Telecommunication Standard) BRAN (Broadband Radio Access Network) includes a short-range high-data-rate communications system called “HIPERLAN type 2” (HIPERLAN/2). HIPERLAN/2 may be used to transport Internet Protocol (IP) packets, and will also be capable to act as a wireless Asynchronous Transfer Mode (ATM) system, as well as a public access system, e.g. with an interface to the Universal Mobile Telecommunications System (UMTS). The physical layer of HIPERLAN/2 is based on OFDM, with a guard interval in the form of a cyclic prefix. Other WLAN systems based on OFDM have been standardized by ARIB in Japan (MMAC and its extensions), and by IEEE in the US (IEEE802.11a and its extensions).
In pilot-assisted channel estimation schemes for OFDM, known symbols are transmitted on given subchannels and time instants for training purposes; for example, in systems according to the HIPERLAN/2 or to the IEEE802.11a standard, there are two full OFDM pilot symbols preceding every burst of data-carrying OFDM symbols. The principle of decision-directed approaches for OFDM is quite similar: before channel estimation, some data symbols are being decided; these decided symbols are then treated in the same way as pilot symbols.
The simplest channel estimation method consists in comparing a transmitted pilot symbol with the received value in the respective subchannel. The ratio between these two quantities then yields an estimated subchannel transfer factor. This method is known as the “least-squares estimation”.
It may be useful to exploit correlations inside the channel transfer function, either in the frequency or in the time domain, or both. Assuming, for simplicity, that only correlations in the frequency domain shall be exploited in the OFDM signal, the characteristics of the channel transfer function over frequency can be regarded as a “band-limited” process. Band-limited means here that the transformation of the channel transfer function into the time-domain yields a CIR of limited length, i.e. the CIR length is substantially smaller than the OFDM symbol length. This usually holds for OFDM transmission systems.
Therefore, correlations in the frequency-domain may be exploited by means of an appropriate filter. Ideally, this filter, which is called a “channel estimation filter”, should be perfectly adapted to the band-limited channel frequency response. This means that the filter should be designed in such a way that the spectrum of its impulse response displays the same band-limitation as the channel frequency response. Hence, an appropriate filter design requires knowledge of the channel excess delay, which specifies said band limitation.
An example of the use of channel estimation filters to improve the quality of channel estimation can be found in the paper by V. Mignone and A. Morello titled “CD3-OFDM: A Novel Demodulation Scheme for Fixed and Mobile Receivers”, IEEE Trans. Comm., vol. 44, No. 9, pp. 1144-1151, September 1996. According to this scheme, which uses a decision-directed coherent demodulation, received signals are fed back after they have been corrected by means of a channel coding scheme (which needs to be fairly powerful in order to ensure stability). Two types of appropriate filters are discussed in this paper. The first one has a pre-set bandwidth which is flat in the time-domain (and is of the order of the guard interval): such a filter is therefore not matched to the actual channel excess delay as it optimally should. The second one has a bandwidth which is adaptively determined after the receiver has calculated the CIR by Fourier-transforming the CTF: but this conversion from the frequency-domain to the time-domain is computationally expensive.
Besides the purpose of channel estimation filtering, the channel correlations in the frequency-domain may also be exploited for link-adaptation purposes. “Link-adaptation” means that one or more channel-characterizing parameters are used to select an appropriate modulation and coding scheme for transmission. In particular, the degree of such correlations may serve as one such channel-characterizing parameter.
An example of this approach can be found in the paper by S. Muneta et al. titled “A New Frequency-Domain Link Adaptation Scheme for Broadband OFDM Systems”, belonging to the Proceedings of the 50th IEEE Vehicular Technology Conference (VTC 1999-Fall), pp. 253-257, Amsterdam, The Netherlands, September 1999. In this paper, a link-adaptation algorithm is proposed, in which two pieces of link information are used to adapt coding rate and modulation scheme of the current radio link in a HIPERLAN/2-type system. These pieces of information are two functions, the values of which depend on both the excess delay and the Signal-to-Noise Ratio (SNR) of the channel. These functions are calculated from the amplitudes of frequency-domain samples of the received preamble. But these functions are defined in a more or less heuristic fashion, and do not take into account the phase of said frequency-domain samples, so that this approach does not perform reliably.